The increasingly commonplace use of flat panel displays operated at ever high refresh rates has spurred a corresponding increasing use of frame rate up-conversion to increase the frame rates of video streams of frames of motion videos to match those refresh rates. Various forms of video interpolation have been devised to generate the additional frames required in such up-conversions.
Earlier forms of video interpolation largely employed various averaging techniques to generate pixel color values for the pixels of interpolated frames from corresponding pixels of adjacent base frames. It was expected that the motion of objects between adjacent base frames could be accommodated by such averaging techniques. However, increases in rates of motion of objects in typical motion videos coupled with increases in pixel resolution in both the motion videos and the displays have made such approaches less desirable due to resulting visual artifacts.
Thus, current forms of video interpolation employ various techniques to specifically detect and characterize the motion of objects between adjacent base frames. In particular, changes in position of the location of pixel color values determined to represent moving objects are detected between adjacent base frames, and motion vectors are derived to describe such changes. Those motion vectors are then employed to determine correct positions among the pixels of interpolated frames at which to locate those pixel color values in an effort to correctly position the moving objects in the interpolated frames.
However, errors can occur in such approaches to video interpolation, including errors in which areas of relatively closely matching pixel color values are incorrectly determined to represent moving objects, in which other pixel color values that represent moving objects are not determined to represent moving objects, and/or in which motion vectors inaccurately indicate direction and/or magnitude of movement. Such errors can cause various visual artifacts in the interpolated frames, including lack of inclusion of some or all of a moving object, inclusion of duplicate portions of a moving object, an apparent stretching of a moving object, an apparent breaking apart of a moving object, etc.
Given the often significantly high frame rates to which motion videos are up-converted, the visual presentation of some of such artifacts may go unnoticed. However, the human visual system (HVS) makes considerable use of edge detection as part of identifying objects such that the visual presentation of artifacts that add and/or remove edges that an object would ordinarily have is often readily noticed and can be very distracting.